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ORCIDJing-Hao Xue
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Publications
- 2024
[j129]Xiaoxu Li, Zijie Guo, Rui Zhu
, Zhanyu Ma, Jun Guo, Jing-Hao Xue:
A simple scheme to amplify inter-class discrepancy for improving few-shot fine-grained image classification. Pattern Recognit. 156: 110736 (2024)- 2023
- [j104]Zhanyu Ma, Xiaoou Lu, Jiyang Xie, Zhen Yang, Jing-Hao Xue, Zheng-Hua Tan, Bo Xiao, Jun Guo:
On the Comparisons of Decorrelation Approaches for Non-Gaussian Neutral Vector Variables. IEEE Trans. Neural Networks Learn. Syst. 34(4): 1823-1837 (2023) - 2022
- [j100]Jiyang Xie, Zhanyu Ma, Jianjun Lei, Guoqiang Zhang, Jing-Hao Xue, Zheng-Hua Tan, Jun Guo:
Advanced Dropout: A Model-Free Methodology for Bayesian Dropout Optimization. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 4605-4625 (2022) - 2021
- [j85]Xiaoxu Li, Dongliang Chang, Zhanyu Ma, Zheng-Hua Tan, Jing-Hao Xue, Jie Cao, Jun Guo:
Deep InterBoost networks for small-sample image classification. Neurocomputing 456: 492-503 (2021) - [j80]Xiaoxu Li, Liyun Yu, Xiaochen Yang, Zhanyu Ma, Jing-Hao Xue, Jie Cao, Jun Guo:
ReMarNet: Conjoint Relation and Margin Learning for Small-Sample Image Classification. IEEE Trans. Circuits Syst. Video Technol. 31(4): 1569-1579 (2021) - [j77]Jiyang Xie, Zhanyu Ma, Jing-Hao Xue, Guoqiang Zhang, Jian Sun, Yinhe Zheng, Jun Guo:
DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for Uncertainty Inference in Image Recognition. IEEE Trans. Image Process. 30: 9208-9219 (2021) - 2020
- [j59]Xiaoxu Li, Dongliang Chang, Zhanyu Ma, Zheng-Hua Tan, Jing-Hao Xue, Jie Cao, Jingyi Yu, Jun Guo:
OSLNet: Deep Small-Sample Classification With an Orthogonal Softmax Layer. IEEE Trans. Image Process. 29: 6482-6495 (2020) - [j56]Zhanyu Ma, Jiyang Xie, Yuping Lai, Jalil Taghia, Jing-Hao Xue, Jun Guo:
Insights Into Multiple/Single Lower Bound Approximation for Extended Variational Inference in Non-Gaussian Structured Data Modeling. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2240-2254 (2020) - [i22]Xiaoxu Li, Dongliang Chang, Zhanyu Ma, Zheng-Hua Tan, Jing-Hao Xue, Jie Cao, Jingyi Yu, Jun Guo:
OSLNet: Deep Small-Sample Classification with an Orthogonal Softmax Layer. CoRR abs/2004.09033 (2020) - [i19]Xiaoxu Li, Liyun Yu, Xiaochen Yang, Zhanyu Ma, Jing-Hao Xue, Jie Cao, Jun Guo:
ReMarNet: Conjoint Relation and Margin Learning for Small-Sample Image Classification. CoRR abs/2006.15366 (2020) - [i17]Jiyang Xie, Zhanyu Ma, Guoqiang Zhang, Jing-Hao Xue, Zheng-Hua Tan, Jun Guo:
Advanced Dropout: A Model-free Methodology for Bayesian Dropout Optimization. CoRR abs/2010.05244 (2020) - [i16]Jiyang Xie, Zhanyu Ma, Jing-Hao Xue, Guoqiang Zhang, Jun Guo:
DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for Uncertainty Inference. CoRR abs/2011.08595 (2020) - 2019
- [j51]Fangyi Zhu, Zhanyu Ma, Xiaoxu Li, Guang Chen, Jen-Tzung Chien, Jing-Hao Xue, Jun Guo:
Image-text dual neural network with decision strategy for small-sample image classification. Neurocomputing 328: 182-188 (2019) - [c9]Jiyang Xie, Zhanyu Ma, Guoqiang Zhang, Jing-Hao Xue, Zheng-Hua Tan, Jun Guo:
Soft Dropout And Its Variational Bayes Approximation. MLSP 2019: 1-6 - 2018
- [j38]Zhanyu Ma, Jing-Hao Xue, Arne Leijon, Zheng-Hua Tan, Zhen Yang, Jun Guo:
Decorrelation of Neutral Vector Variables: Theory and Applications. IEEE Trans. Neural Networks Learn. Syst. 29(1): 129-143 (2018) - [c6]Jiyang Xie, Zhanyu Ma, Guoqiang Zhang, Jing-Hao Xue, Jen-Tzung Chien, Zhiqing Lin, Jun Guo:
Balson: Bayesian least squares Optimization with Nonnegative L1-norm Constraint. MLSP 2018: 1-6 - [i4]Jiyang Xie, Zhanyu Ma, Guoqiang Zhang, Jing-Hao Xue, Jen-Tzung Chien, Zhiqing Lin, Jun Guo:
BALSON: Bayesian Least Squares Optimization with Nonnegative L1-Norm Constraint. CoRR abs/1807.02795 (2018) - [i3]Jiyang Xie, Jiaxin Guo, Zhanyu Ma, Jing-Hao Xue, Qie Sun, Hailong Li, Jun Guo:
SEA: A Combined Model for Heat Demand Prediction. CoRR abs/1808.00331 (2018) - 2017
- [i1]Zhanyu Ma, Jing-Hao Xue, Arne Leijon, Zheng-Hua Tan, Zhen Yang, Jun Guo:
Decorrelation of Neutral Vector Variables: Theory and Applications. CoRR abs/1705.10524 (2017)
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